Security concerns on machine learning solutions for 6G networks in mmWave beam prediction FO Catak, M Kuzlu, E Catak, U Cali, D Unal Physical Communication 52, 101626, 2022 | 33 | 2022 |
Adversarial machine learning security problems for 6G: mmWave beam prediction use-case E Catak, FO Catak, A Moldsvor 2021 IEEE International Black Sea Conference on Communications and …, 2021 | 23 | 2021 |
Defensive distillation-based adversarial attack mitigation method for channel estimation using deep learning models in next-generation wireless networks FO Catak, M Kuzlu, E Catak, U Cali, O Guler IEEE Access 10, 98191-98203, 2022 | 17 | 2022 |
An efficient transceiver design for superimposed waveforms with orthogonal polynomials E Catak, L Durak-Ata 2017 IEEE International Black Sea Conference on Communications and …, 2017 | 15 | 2017 |
Multi-user shared access in massive machine-type communication systems via superimposed waveforms E Çatak, F Tekce, O Dizdar, L Durak-Ata Physical Communication 37, 100896, 2019 | 12 | 2019 |
Waveform design considerations for 5G wireless networks E Çatak, L Durak-Ata Towards 5G Wireless Networks-A Physical Layer Perspective, 27-48, 2016 | 12 | 2016 |
Adversarial security mitigations of mmWave beamforming prediction models using defensive distillation and adversarial retraining M Kuzlu, FO Catak, U Cali, E Catak, O Guler International Journal of Information Security 22 (2), 319-332, 2023 | 10 | 2023 |
Adaptive filterbank-based multi-carrier waveform design for flexible data rates E Çatak, L Durak-Ata Computers & electrical engineering 61, 184-194, 2017 | 8 | 2017 |
Filtered multitone system for users with different data rates at 5G wireless networks E Çatak, LD Ata 2016 24th Signal Processing and Communication Application Conference (SIU …, 2016 | 7 | 2016 |
Transceiver design for GFDM with hexagonal time–frequency allocation using the polyphase decomposition E Catak, A Moldsvor, M Derawi Electronics 9 (11), 1862, 2020 | 4 | 2020 |
Security hardening of intelligent reflecting surfaces against adversarial machine learning attacks FO Catak, M Kuzlu, H Tang, E Catak, Y Zhao IEEE Access 10, 100267-100275, 2022 | 3 | 2022 |
The effect of codebook design on the BER performance of MTC systems employing SCMA F Tekçe, E Çatak, UE Ayten, L Durak-Ata 2018 26th Signal Processing and Communications Applications Conference (SIU …, 2018 | 3 | 2018 |
Practical implementation of the combinational cooperative detection method E Çatak, S Erküçük Wireless Personal Communications 80, 723-738, 2015 | 3 | 2015 |
Security and Privacy Concerns in Next-Generation Networks Using Artificial Intelligence-Based Solutions: A Potential Use Case M Kuzlu, FO Catak, Y Zhao, S Sarp, E Catak Wireless Networks: Cyber Security Threats and Countermeasures, 205-226, 2023 | 2 | 2023 |
Mitigating attacks on artificial intelligence-based spectrum sensing for cellular network signals FO Catak, M Kuzlu, S Sarp, E Catak, U Cali 2022 IEEE Globecom Workshops (GC Wkshps), 1371-1376, 2022 | 2 | 2022 |
Superimposed waveforms for users with high data rate at 5G wireless networks E Çatak, L Durak-Ata 2017 25th Signal Processing and Communications Applications Conference (SIU …, 2017 | 2 | 2017 |
The effect of secondary user locations on the cooperative detection performance E Çatak, S Erküçük 2012 20th Signal Processing and Communications Applications Conference (SIU …, 2012 | 2 | 2012 |
Defending AI-Based Automatic Modulation Recognition Models Against Adversarial Attacks H Tang, FO Catak, M Kuzlu, E Catak, Y Zhao IEEE Access, 2023 | 1 | 2023 |
Security Concerns on Machine Learning Solutions for 6G Networks in mmWave Beam Prediction F Ozgur Catak, E Catak, M Kuzlu, U Cali, D Unal arXiv e-prints, arXiv: 2105.03905, 2021 | 1 | 2021 |
Enhanced physical layer security by OFDM signal transmission in fractional Fourier domains E Çatak, LD Ata, HA Mantar 2015 23nd Signal Processing and Communications Applications Conference (SIU …, 2015 | 1 | 2015 |